@Article{jihpp.2021.027280,
AUTHOR = {Pengzhi Xu, Zetian Mai, Yuhao Lin, Zhen Guo, Victor S. Sheng},
TITLE = {A Survey on Binary Code Vulnerability Mining Technology},
JOURNAL = {Journal of Information Hiding and Privacy Protection},
VOLUME = {3},
YEAR = {2021},
NUMBER = {4},
PAGES = {165--179},
URL = {http://www.techscience.com/jihpp/v3n4/47056},
ISSN = {2637-4226},
ABSTRACT = {With the increase of software complexity, the security threats faced by 
the software are also increasing day by day. So people pay more and more 
attention to the mining of software vulnerabilities. Although source code has rich 
semantics and strong comprehensibility, source code vulnerability mining has been 
widely used and has achieved significant development. However, due to the 
protection of commercial interests and intellectual property rights, it is difficult to 
obtain source code. Therefore, the research on the vulnerability mining technology 
of binary code has strong practical value. Based on the investigation of related 
technologies, this article firstly introduces the current typical binary vulnerability 
analysis framework, and then briefly introduces the research background and 
significance of the intermediate language; with the rise of artificial intelligence, a 
large number of machine learning methods have been tried to solve the problem of 
binary vulnerability mining. This article divides the current related binary 
vulnerabilities mining technology into traditional mining technology and machine 
learning mining technology, respectively introduces its basic principles, research 
status and existing problems, and briefly summarizes them. Finally, based on the 
existing research work, this article puts forward the prospect of the future research 
on the technology of binary program vulnerability mining.},
DOI = {10.32604/jihpp.2021.027280}
}